Calculate the matrix effect by comparing the slope of a solvent-based calibration curve with one or more matrix-matched calibration. The matrix effect is expressed as signal suppression/enhancement ratio.

## Arguments

- object
an object of class '

`calibration`

' obtained from analyzing standard solutions of different concentration (solvent calibration data).- ...
additional objects of the same type obtained from matrix-matched calibration data.

## Value

The magnitude of a matrix effect is estimated by subtracting the slope of a matrix-matched calibration from that of the solvent-based calibration. The difference is divided by the slope of the solvent-based calibration.

## Details

Matrix effects or signal suppression/enhancement ratios should be evaluated during analytical method development to avoid over- or underestimation of sample concentrations. In addition, signal suppression/enhancement ratios may help to justify the validity of a regular solvent calibration as opposed to matrix-matched calibrations. This may be the case if matrix effects or signal suppression/enhancement ratios are close to measurement repeatability.

## See also

Other calibration:
`calibration()`

,
`din32645`

,
`icp`

,
`neitzel2003`

,
`phenolics`

,
`weight_select()`

## Examples

```
data(din32645)
din <- calibration(Area ~ Conc, data = din32645)
m32645 <- din32645
m32645$Area <- din32645$Area * 1.5
matrix <- calibration(Area ~ Conc, data = m32645)
matrix_effect(din, matrix)
#> din - matrix
#> 0.5
```